Lecture Notes on Design & Analysis of Algorithms G P Raja Sekhar Department of Mathematics I I T Kharagpur Acknowledgements : Ahmad Abdullah‚ Pronoy Sikdar‚ Anshul Kamra‚ Sugam Agrawal & Students of DAA course 2006-07‚ Data Structures & Algorithms 2006-07. BUBBLE SORT The bubble sort is the oldest and simplest sort in use. The bubble sort works by comparing each item in the list with the item next to it‚ and swapping them if required. The algorithm repeats this process until it makes a pass
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1997 describes a combined genetic algorithm and slicing approach for floorplan area optimization during the early stage of integrated circuit design. It applies a partition procedure to reduce the complexity routing problem. Genetic Algorithm (GA) is wide applied in almost any field‚ including solving FLP. Tam 1992 introduced the coding of layouts as a string of characters of finite length and used a fixed slicing tree structure defined by a clustering algorithm to represent a layout as a chromosome
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modern computing and Vedic Mathematics converge. Need For Efficient Multiplication Algorithm: • Use of numerical methods is prevalent in most software algorithms. Such applications demand an efficient code for basic mathematical operations‚ one of them being multiplication. • Real Time Systems demand instantaneous response to environmental variables and quick execution of taken decision. • Multiplication algorithms find applications in Digital Signal Processing (DSP) for discrete Fourier transforms
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Parallelization of PageRank and HITS Algorithm on CUDA Architecture ‡ ‡ Kumar Ishan‚ Mohit Gupta‚ Naresh Kumar‚ Ankush Mittal† ‡ Department of electronics & Computer Engineering‚ Indian Institute of Technology‚ Roorkee‚ India. {kicomuec‚ mickyuec‚ naresuec‚ ankumfec}@iitr.ernet.in Abstract Efficiency of any search engine mostly depends on how efficiently and precisely it can determine the importance and popularity of a web document. Page Rank algorithm and HITS algorithm are widely known approaches
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Complexities! Good Fair Poor Searching Algorithm Data Structure Time Complexity Depth First Search (DFS) Graph of |V| vertices and |E| edges Graph of |V| vertices and |E| edges Sorted array of n elements Array - O(|E| + |V|) O(|V|) - O(|E| + |V|) O(|V|) O(log(n)) O(log(n)) O(1) O(n) O(n) O(1) Graph with |V| vertices and |E| edges O((|V| + |E|) log |V|) O((|V| + |E|) log |V|) O(|V|) Graph with |V| vertices and |E| edges O(|V|^2) O(|V|^2) O(|V|) Graph with |V| vertices and
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Vision Singapore‚ 7-10th December 2010 tinySLAM : a SLAM Algorithm in less than 200 lines C-Language Program Bruno STEUX - Oussama EL HAMZAOUI Robotics Center. Mines ParisTech Paris‚ FRANCE {bruno.steux‚oussama.el_hamzaoui}@mines-paristech.fr Abstract—This paper presents a Laser-SLAM algorithm which can be programmed in less than 200 lines C-language program. The first idea aimed to develop and implement a simple SLAM algorithm providing good performances without exceeding 200 lines in
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Differential Evolution Algorithm for Solving Multi-Stages Assignment Problem: a case study of chicken transportation. I. Introduction The transportation in this case study is a chicken transportation from chicken farm to egg farm. There are 4 types of truck which are ten-wheel truck‚ eight-wheel truck‚ modified four-wheel truck and ordinary four-wheel truck. Each type of truck has different capacity moreover each hen’s farm has different in quantity supplied as same as each egg’s farm also have
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centers. 6 3.1 Runtime energy consumption calculation model 6 3.2 Energy-Aware Scheduling Algorithm 7 3.2.1 Energy Aware Scheduling by Minimizing Duplication algorithm 8 3.2.2 Experimental results and analysis 9 3.3 Dynamic provisioning and Load dispatching 9 3.3.1 Energy aware server provisioning 10 3.3.2 Forecast-based provisioning 10 3.3.2.1 Short-term load forecasting 10 3.3.3 Load Dispatching Algorithm 12 3.3.3.1 Load balancing 12 3.3.4 Evaluation of forecast provisioning and
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Structures‚ Algorithm Analysis: Table of Contents 页码，1/1 Data Structures and Algorithm Analysis in C by Mark Allen Weiss PREFACE CHAPTER 1: INTRODUCTION CHAPTER 2: ALGORITHM ANALYSIS CHAPTER 3: LISTS‚ STACKS‚ AND QUEUES CHAPTER 4: TREES CHAPTER 5: HASHING CHAPTER 6: PRIORITY QUEUES (HEAPS) CHAPTER 7: SORTING CHAPTER 8: THE DISJOINT SET ADT CHAPTER 9: GRAPH ALGORITHMS CHAPTER 10: ALGORITHM DESIGN TECHNIQUES CHAPTER 11: AMORTIZED ANALYSIS mk:@MSITStore:K:\Data.Structures.and.Algorithm.Analysis
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efficient operation of both primary and cognitive users. In this paper‚ an algorithm is used to dynamically control transmission power‚ which is capable of achieving reasonably good solutions fast enough in order to guarantee an acceptable level of performance for CU without degrading the performance of primary user(s). Genetic Algorithm is used to enhance the convergence time. Keywords: Cognitive radio‚ Genetic Algorithm‚ Power allocation‚ Quality of Service. I. INTRODUCTION The recent rapid
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